Triple
T20468568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cliff Gorman |
E502120
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Lenny |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lenny | Statement: [Cliff Gorman, notableWork, Lenny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenny Context triple: [Cliff Gorman, notableWork, Lenny]
-
A.
Lenny
Lenny is a science fiction short story by Isaac Asimov, featuring one of his early robot characters and exploring themes of robotics and human-robot interaction.
-
B.
Lenny
chosen
Lenny is a 1974 American biographical drama film about controversial comedian Lenny Bruce, directed by Bob Fosse and starring Dustin Hoffman.
-
C.
Lenny
Lenny is the nickname and given name of Lenny Belardo, the fictional young American pope from the television series "The Young Pope."
-
D.
Lenny
Lenny is a gentle, vegetarian great white shark from the animated film "Shark Tale" who struggles against his family's expectations to be a fierce predator.
-
E.
Lenny
Lenny is a fictional character from Jake Arnott’s crime novel "The Long Firm," set in London’s 1960s underworld.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6995e71c08190911fadbc433f0f4d |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.